ABSTRACT ? BIOINFORMATICS SHARED RESOURCE The Bioinformatics (BIn) shared resource, a core function of the Duke Cancer Institute (DCI), serves as a centralized resource for expertise in applied and theoretical cancer bioinformatics, genomics, computational biology, machine learning and statistical genetics. The faculty and staff members of this shared resource support DCI members across the continuum of research, including experimental and statistical design for genomic studies, complex genomic data management, integration of diverse data sets, computing and statistical analysis, and machine learning. The shared resource provides support for investigator-generated data as well as retrospective data from research databases (e.g., GDC [large datasets like TCGA] or dbGAP). The resource?s mission is to provide high-quality, service-oriented, coordinated and cost-efficient bioinformatics support and infrastructure for DCI members. Emphasis is placed on facilitating increased collaborations across DCI programs and other DCI shared resources. The mission of this shared resource is addressed within the framework of adherence to 3 principles: 1- sound data provenance and statistical principles, 2- literate programming, and 3- reproducible analysis. The BIn shared resource provides and runs standardized genomic analysis pipelines (e.g., germline, tumor and cell-free DNA-Seq, bulk and single-cell RNA-Seq, CHiP-Seq, and sequencing of T-Cell Receptor repertoire and microbiome). These pipelines are constructed on the basis of state-of-the-art published tools, maintained under strict source code version control and designed to be extensible and deployable in a scalable fashion on local servers and cloud services. The philosophy of the BIn shared resource is that the scope of scientific discovery and rigor should neither be limited nor compromised due to lack of appropriate and adequate statistical methodology or computational tools. When needed and appropriate, the faculty and staff of the shared resource extend or revise existing or develop de novo methods and computational tools to enable DCI members to address scientific questions with requisite rigor and efficiency. In addition to computing and analysis support, the shared resource provides extensive support for writing of scientific abstracts and manuscripts, as well as grant proposals. The BIn shared resource also serves as a liaison and facilitator between DCI members and other DCI shared resources (e.g., the Biostatistics, Functional Genomics, Information Systems, and BioRepository and Precision Pathology Center Shared Resources). The research support, services and resources of the BIn shared resource are provided exclusively to DCI members. In 2018, the BIn shared resource provided services to 53 investigators, 100% of whom were DCI members, accounting for 100% of total usage, from all 8 DCI Research Programs. Use of this shared resource by DCI members contributed to 178 publications over the project period, 41 of which were in high impact journals, demonstrating the value of services offered by the resource.